A Practical Introduction to PySpark Window Functions

PySpark's standard groupBy() function aggregates data but collapses the original rows, losing individual record detail. Window functions solve this by allowing calculations across related records while preserving each original row. These functions are defined using a window specification that partitions data with `partitionBy()` and orders it with `orderBy()`. The content provides practical code examples for common tasks such as ranking rows within groups, calculating running totals, and comparing a row's value with the previous one.